Integrating artificial intelligence in nanomembrane systems for advanced water desalination

The increasing global demand for clean drinking water calls for innovative approaches to optimize desalination processes, making them more sustainable and efficient. The integration of nanotechnology with artificial intelligence (AI)—particularly through machine learning and neural networks—is drivi...

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Main Authors: Anbarasu Krishnan, Thanigaivel Sundaram, Beemkumar Nagappan, Yuvarajan Devarajan, Bhumika
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Results in Engineering
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Online Access:http://www.sciencedirect.com/science/article/pii/S2590123024015755
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author Anbarasu Krishnan
Thanigaivel Sundaram
Beemkumar Nagappan
Yuvarajan Devarajan
Bhumika
author_facet Anbarasu Krishnan
Thanigaivel Sundaram
Beemkumar Nagappan
Yuvarajan Devarajan
Bhumika
author_sort Anbarasu Krishnan
collection DOAJ
description The increasing global demand for clean drinking water calls for innovative approaches to optimize desalination processes, making them more sustainable and efficient. The integration of nanotechnology with artificial intelligence (AI)—particularly through machine learning and neural networks—is driving the development of advanced nanomembranes with enhanced performance and reliability. AI algorithms embedded in these nanomembrane systems enable real-time monitoring, adaptive responses to changing conditions, and proactive maintenance strategies. For instance, AI can optimize energy consumption, mitigate membrane fouling, and extend membrane lifespan. As these AI-enhanced systems operate, they continuously learn and improve their efficiency under diverse conditions. This technology also supports decentralized water solutions by enabling remote management, reducing the need for on-site personnel, and expanding access to clean water in remote areas. AI-driven systems can analyze real-time data and make informed decisions, ensuring consistent and sustainable operation. However, challenges remain, such as the development of desalination-specific AI algorithms, ensuring scalability and compatibility, and addressing data privacy and security concerns. While the convergence of AI and nanomembrane technology holds immense potential for revolutionizing water desalination, ongoing research and design efforts are essential to fully realize its capabilities in the coming years.
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spelling doaj-art-6e973d2a961b46c7bb9e032caed49f3c2025-08-20T02:34:36ZengElsevierResults in Engineering2590-12302024-12-012410332110.1016/j.rineng.2024.103321Integrating artificial intelligence in nanomembrane systems for advanced water desalinationAnbarasu Krishnan0Thanigaivel Sundaram1Beemkumar Nagappan2Yuvarajan Devarajan3 Bhumika4Department of Bioinformatics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Thandalam, Chennai, Tamil Nadu, 602 105, IndiaDepartment of Biotechnology, Faculty of Science & Humanities, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu 603203, IndiaDepartment of Mechanical Engineering, Jain Deemed to be university, Bengaluru, IndiaDepartment of Mechanical Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Thandalam, Chennai, Tamil Nadu, 602 105, India; Corresponding author.Centre for Research Impact and Outcome, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, 140401, Punjab, IndiaThe increasing global demand for clean drinking water calls for innovative approaches to optimize desalination processes, making them more sustainable and efficient. The integration of nanotechnology with artificial intelligence (AI)—particularly through machine learning and neural networks—is driving the development of advanced nanomembranes with enhanced performance and reliability. AI algorithms embedded in these nanomembrane systems enable real-time monitoring, adaptive responses to changing conditions, and proactive maintenance strategies. For instance, AI can optimize energy consumption, mitigate membrane fouling, and extend membrane lifespan. As these AI-enhanced systems operate, they continuously learn and improve their efficiency under diverse conditions. This technology also supports decentralized water solutions by enabling remote management, reducing the need for on-site personnel, and expanding access to clean water in remote areas. AI-driven systems can analyze real-time data and make informed decisions, ensuring consistent and sustainable operation. However, challenges remain, such as the development of desalination-specific AI algorithms, ensuring scalability and compatibility, and addressing data privacy and security concerns. While the convergence of AI and nanomembrane technology holds immense potential for revolutionizing water desalination, ongoing research and design efforts are essential to fully realize its capabilities in the coming years.http://www.sciencedirect.com/science/article/pii/S2590123024015755Artificial intelligenceSustainable practicesRenewableEnergy
spellingShingle Anbarasu Krishnan
Thanigaivel Sundaram
Beemkumar Nagappan
Yuvarajan Devarajan
Bhumika
Integrating artificial intelligence in nanomembrane systems for advanced water desalination
Results in Engineering
Artificial intelligence
Sustainable practices
Renewable
Energy
title Integrating artificial intelligence in nanomembrane systems for advanced water desalination
title_full Integrating artificial intelligence in nanomembrane systems for advanced water desalination
title_fullStr Integrating artificial intelligence in nanomembrane systems for advanced water desalination
title_full_unstemmed Integrating artificial intelligence in nanomembrane systems for advanced water desalination
title_short Integrating artificial intelligence in nanomembrane systems for advanced water desalination
title_sort integrating artificial intelligence in nanomembrane systems for advanced water desalination
topic Artificial intelligence
Sustainable practices
Renewable
Energy
url http://www.sciencedirect.com/science/article/pii/S2590123024015755
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